In​ the​ field​ of​ medicine,​ natural​ treatments​ are​ becoming ​increasingly ​vital ​towards ​the ​cure ​of ​cancer. Zhu et al. wanted to investigate the effects of lettuce extract on cancer cell survival and proliferation. They used an adenocarcinoma cell line, COLO320DM, to determine whether crude extract from a lettuce species called Niuli​ Lactucis Agrestibus​ would affect cancer cell survival, migration, and proliferation. They found that Niuli extract inhibited cancer cell survival, increased expression of cell cycle inhibitors p21 and p27, and inhibited migration. However, Niuli extract did not have these effects on healthy cells. This work reveals important findings about a potential new source of anti-colorectal cancer compounds.

Ant invasion causes damage exceeding $5 billion annually in North America. In this study, Ambati and Duvvuri aim to identify natural products with ant-repelling properties using a custom ring apparatus designed to quantify ant-repellence. They report that cinnamon and lemon were the most effective ant repellents of the tested products. These data suggest that compounds found in non-toxic household products, such as cinnamon oil and lemon juice, could be used in low-dose combinations as potent, effective, eco-friendly, and safe ant repellents.

Due to the increase in antimicrobial resistance, alternative medicinal therapies are being explored. Studies have shown that honey and ginger alone have antimicrobial effects on the genera Staphylococcus and Escherichia, including S. epidermidis and E. coli. The authors of this study tested whether a honey-ginger supplement, Jengimiel™, could be used as an antimicrobial agent against S. epidermidis and E. coli K-12.

The study discusses the relationship between bacterial species and the human gut microbiome, emphasizing the role of quorum sensing molecules in bacterial communication and its implications for health. Authors investigated the impact of bacterial supernatants from Escherichia coli (E. coli) on the growth of new E. coli and Enterobacter aerogenes (E. aerogenes) cultures.

Quorum sensing (QS) is the process in which bacteria recognize and respond to the surrounding cell density, and it can be inhibited by certain antimicrobial substances. This study showed that illumination intensity data is insufficient for evaluating QS activity without proper statistical modeling. It concluded that modeling illumination intensity through time provides a more accurate evaluation of QS activity than conventional cross-sectional analysis.

Reinforcement learning (RL) is a form of machine learning that can be harnessed to develop artificial intelligence by exposing the intelligence to multiple generations of data. The study demonstrates how reply buffer reward mechanics can inform the creation of new pruning methods to improve RL efficiency.

Here, recognizing a declining supply of rock phosphate, as well as its role in crop fertilization, the authors investigated a fungus that forms a symbiotic relationship with many crops. They found that symbiosis between the fungus and common bean plant increased the affinity of the plant towards absorbing nutrients as evidenced by lower root-to-shoot ratios in beans planted in soil with various concentrations of phosphorous and salinity.

The authors investigate whether Western Bluebirds and other perching birds consume eggshells, as a source of calcium, at a greater rate before reproduction and during nest building when they are unable to store calcium.

The purpose of the study was to determine whether graph-based machine learning techniques, which have increased prevalence in the last few years, can accurately classify data into one of many clusters, while requiring less labeled training data and parameter tuning as opposed to traditional machine learning algorithms. The results determined that the accuracy of graph-based and traditional classification algorithms depends directly upon the number of features of each dataset, the number of classes in each dataset, and the amount of labeled training data used.

This study investigates the feasibility of using long-range radio communication in a busy city environment in order to begin better understanding how the Internet of Things might be implemented into smart cities.